Mainframes still run core processing for many banks, insurers and governments. They are reliable, but skills are scarce, change is slow and data is hard to reach. So programs move workloads to modern platforms, piece by piece.
The hardest question
Every migration eventually faces one question: does the new system produce exactly the same results as the old one? Interest calculations, fee rules, rounding, date handling and decades of special cases all have to match. Today this is often checked with spreadsheets and sampled records.
Sampling is not proof
A sample of a few thousand records can pass while a rare but important case fails, such as an account opened on a leap day or a fee waived under an old promotion. These defects surface after cutover, in front of customers.
Every record compared, every difference explained.
Compare everything, explain differences
A better approach compares every record from parallel runs, field by field. Tolerance rules absorb harmless differences like formatting or ordering. Every remaining difference is classified: cosmetic, or a genuine logic break. Teams fix the breaks and rerun until the differences that matter reach zero.
Make cutover a decision
When parity is measured this way, the cutover meeting changes. Instead of debating confidence, business owners and auditors review evidence: run results, remaining differences and their explanations. Cutover becomes a documented decision rather than a leap of faith.
Design for parallel running
Parity testing works best when it is planned from the start. Old and new systems need to run the same inputs, outputs need stable identifiers to match records, and environments must allow repeated runs. Building these in early costs little and saves months later.
Explain differences in plain language
Raw difference reports overwhelm business owners. Grouping differences by cause, and describing each cause in plain language with examples, lets the right people make decisions quickly. Engineers fix the logic; business owners decide what is acceptable.
QAO ParityCheck is an accelerator built for exactly this: reading legacy layouts, comparing outputs at scale and producing sign-off evidence.